Abstract: A trace anomaly grouping and visualization technique logically groups traces with anomalies to cases to enable software developers to monitor, diagnose and visualize the anomalies, as well as to solve the anomalies during application development and production. A client library of an investigative platform collects signals from traces (trace signal information). The technique organizes (groups) related trace signals of methods with anomalies (e.g., exceptions, performance abnormalities such as slowness) into datasets (denominated as “cases”) based on common cause for an anomaly and correlates the signals to identify a case. The collected information may be used to differentiate between root causes of the anomalies using a comparative visualization of traces displayed on a standard user interface of the investigative platform.

Abstract: Based on replay of a thread, one implementation observes an influx of a value of a memory cell comprising an interaction between the thread and the value of the memory cell at an execution time point in the replaying, and determines whether the value of the memory cell observed from the influx is inconsistent with a prior value of the memory cell as known by the thread at the execution time point. If so, this implementation initiates an indication of a data inconsistency. Based on replay of a plurality of threads, another implementation identifies a memory cell that was accessed by a first thread while a thread synchronization mechanism was active on the first thread. Then, if there was another access to the memory cell by a second thread without use of the thread synchronization mechanism, this implementation initiates an indication of a potential data contention.

Abstract: A specific on-board device, that is any one of a plurality of on-board devices, is configured to acquire the versions of software included in other on-board devices when the power source of a vehicle is turned on. The specific on-board device determines whether or not the versions of the software of all the on-board devices that constitute a vehicle control system are consistent, by comparing the version of the software of the specific on-board device and the versions of the software acquired from the other on-board devices with first consistency information prestored.

Abstract: Techniques are disclosed for generating an execution plan for performing functional tests in a cloud-computing environment. Infrastructure resources and capabilities (e.g., system requirements) may be defined within an infrastructure object (e.g., a resource of a declarative infrastructure provisioner) that stores a code segment that implements the resource or capability. Metadata may be maintained that indicates what particular capabilities are applicable to each infrastructure resource. Using the metadata, the system can generate an execution plan by combining code segments for each resource with code segments defining each capability in accordance with the metadata. The execution plan may include programmatic instructions that, when executed, generate a set of test results. The system can execute instructions that cause the set of test results to be presented at a user device.

Abstract: Disclosed are various embodiments for anti-pattern detection in extraction and deployment of a microservice. A software modernization service is executed to analyze a computing application to identify various applications. When one or more of the application components are specified to be extracted as an independently deployable subunit, anti-patterns associated with deployment of the independently deployable subunit are determined prior to extraction. Anti-patterns may include increases in execution time, bandwidth, network latency, central processing unit (CPU) usage, and memory usage among other anti-patterns. The independently deployable subunit is selectively deployed separate from the computing application based on the identified anti-patterns.

Abstract: One embodiment comprises a stateless container of binaries and a broker. The stateless container of binaries includes a code memory having stored thereon code for a first version of a first functional component of a content management system, the first functional component executable to provide a first version of a service. The broker may be executable to: receive a request for the service from a client application, the request associated with a user of the content management system; determine that the first version of the service is accessible with regard to the user; determine an available first server that hosts the first version of the service; provide an indication of the first version of the service to the client application; and provide an IP address and a port number associated with the available first server to the client application.

Abstract: Novel tools and techniques are provided for implementing object-oriented infrastructure-as-code platform (“OOIACP”) and its functionalities. In various embodiments, an OOIACP may receive a request to perform a function from a requesting device. The OOIACP includes a declarative configuration language (“DCL”)-based infrastructure-as-code (“IAC”) software tool that provides structure and data functionalities and a wrapper tool that provides algorithm and sequence functionalities to the IAC software tool to convert the IAC software tool into an object-oriented programming (“OOP”)-based IAC system. The OOIACP uses a run command to perform the requested function, by identifying classes within a class hierarchy associated with the requested function, and initiating a set of procedures in each identified class. Each class and subclass within the class hierarchy has one or more predefined class behaviors, and each subclass inherits class behaviors of classes to which it belongs and of any intermediate subclasses.

Abstract: A model of an algorithm to be tested is created based on the steps that the algorithm uses to implement a particular function. The model is used by an algorithm verification process to control execution of the application under test. Stubs (small pieces of code) are inserted into the application under test which are used to control execution of the algorithm to determine the result of execution of the algorithm at various locations. The remote stubs enable the testing framework to control execution of the application, stop execution of the application, view data structures associated with the application, freeze system behavior, induce multi-layered dependent sequences, analyze logs, change system flow based on test requests, examine internal data structures as part of the tests, and verify that each method and the combined results of the methods are as expected, based on the original definition of the application algorithm.

Abstract: Artifacts, including parameters are data sets, associated with experiment tasks are stored at an experiment management service. A query specifying a particular value of a parameter and a particular data set is received, and an indication of an experiment result associated with the particular data set and the particular parameter value is provided.

Abstract: A system and method for adapting an errant automated decisioning workflow includes reconfiguring digital abuse or digital fraud logic parameters associated with automated decisioning routes of an automated decisioning workflow in response to identifying an anomalous drift or an anomalous shift in efficacy metrics of the automated decisioning workflow, wherein the automated decisioning workflow includes a plurality of distinct automated decisioning routes that, when applied in a digital threat evaluation of data associated with a target digital event, automatically compute a decision for disposing the target digital event based on a probability digital fraud; simulating, by computers, a performance of the automated decisioning routes in a reconfigured state based on inputs of historical digital event data; calculating simulation metrics based on simulation output data of the simulation; and promoting to an in-production state the automated decisioning workflow having the automated decisioning routes in the rec

Abstract: The present disclosure relates to a method for scheduling a computation graph on heterogeneous computing resources. The method comprises generating an augmented computation graph that includes a first set of replica nodes corresponding to a first node in the computation graph and a second set of replica nodes corresponding to a second node in the computation graph, wherein the replica nodes of the first set are connected by edges to the replica nodes of the second set according to dependency between the first node and the second node in the computation graph, adapting the augmented computation graph to include performance values for the edges, the replica nodes of the first set, and the replica nodes of the second set, and determining a path across the adapted computation graph via one replica node of the first set and one replica node of the second set based on the performance values.

Abstract: Disclosed are systems and methods for trusted and secure application deployment via collective signature verification of the application artifacts. The trusted and secure application deployment may include receiving multiple application artifacts, decoding verifications from at least one cryptographic signature associated with each received artifact, comparing the verifications to a first set of requirements specified in an admission control list, comparing the verifications from a first received artifact to a second set of requirements specified in the verifications of a second received artifact, halting the deployment of the artifacts in response to the decoded verifications not satisfying one or more requirements from the first set of requirements or the second set of requirements, and deploying the artifacts to a set of compute nodes in response to the verifications decoded from the received artifacts satisfying the first set of requirements and the second set of requirements.

Abstract: Disclosed are implementations for software debugging and application development, including a method that includes receiving an instrumentation request, associated with one or more contextual conditions, for application data resulting from execution of an application process on an application system, the application process corresponding to source code with a segment to capture data at a first observability level. The instrumentation request includes information to cause adjustment of the first observability level to a second observability level different from the first observability level.

Abstract: Devices at different geolocations are configured to determine and share information regarding execution of an application under various conditions. Data determined by a user device includes private information, such as screen capture data, location data, or information about the user. The user device processes the data locally, such as by determining performance metrics or other characteristics of execution of the application, and sends this information to a server. The data sent to the server excludes the private information. The server determines additional data associated with execution of the application by devices other than the user device, which may include screen capture data or location data associated with those other devices. The additional data is used in conjunction with the data received from the user device to generate interfaces indicative of performance metrics of the application.

Abstract: A system and method are disclosed for running a plurality of simulation tests on a first machine learning model to obtain a plurality of results that are each produced during a respective simulation test, the first machine learning model gradually trained using first training data historically collected over a period of time, the first training data comprising a plurality of first training data sets each including a subset of first training inputs and first target outputs associated with one of a plurality of points in time during the period of time, determining a simulation test of the plurality of simulation tests at which corresponding results of the first machine learning model satisfy a threshold condition, wherein the threshold condition is based on historical data at a first point in time of the plurality of points in time, identifying a first training data set of the plurality of first training data sets on which the first machine learning model used during the determined simulation test was trained,

Abstract: A code coverage method for an embedded System on Chip (SoC) includes detecting a presence of a utility function in target source code; adding a hook function to the target source code; and recording at least one property of the utility function based on the hook function in a bit array in a memory of the SoC. The method may further include extracting at least one recorded property from bit arrays in the memory; and generating a code coverage report based on an analysis of the extracted properties.

Abstract: A method detects anomalies in a system having sensors for collecting multivariate sensor data including discrete event sequences. The method determines, using a NMT model, pairwise relationships among the sensors based on the data. The method forms sequences of characters into sentences on a per sensor basis, by treating each discrete variable in the sequences as a character in natural language. The method translates, using the NMT, the sentences of source sensors to sentences of target sensors to obtain a translation score that quantifies a pairwise relationship strength therebetween. The method aggregates the pairwise relationships into a multivariate relationship graph having nodes representing sensors and edges denoted by the translation score for a sensor pair connected thereto to represent the pairwise relationship strength therebetween. The method performs a corrective action to correct an anomaly responsive to a detection of the anomaly relating to the sensor pair.

Abstract: A mobile application development environment may be maintained in association with a computing platform. A request to produce a binary of a first mobile application may be processed. The binary and a package configurable to cause the binary to have code-sign credentials associated with a first organization when the binary is uploaded to a mobile application provider may be produced. The binary and the package may be provided to the first organization.

Abstract: Embodiments are disclosed for obtaining a call stack for binaries, where the call stack includes a sequence of frames, and each frame has a “from” address and a “to” address for a call instruction, and for determining basic blocks of instructions for the binaries, where each basic block of instruction has one or more instructions. Further, the embodiments include traversing the call stack to validate from/to address pairs of sequential frames based on control flow routes existing between “from” addresses and “to” addresses of the from/to address pairs, where each from/to address pair has a “from” address of a frame and a “to” address of an immediate previous frame on the call stack.

Abstract: Disclosed is a test engine intended to evaluate the correctness and measure the performance effects of a binary transformation technique. The disclosed system takes source code as input and compiler information/flags as input. The transformation-under-test is applied to the compiler, creating a transformed compiler. A random test case generator residing within the test engine for injecting illegal code structures to modify the project source code, build flags, or compiler's operating environment, thereby creating an unlimited number of input test cases for the compiler. The test engine compiles the source code utilizing both the raw and transformed compilers and compares the results. For example, the test engine renders a pass/fail judgement on the binary transformation based on a metric of near equivalence between the results of the raw compiler and transformed compiler. By using one or more bitmasks, the evaluation process factors in differences attributed to compiler run-time generated artifacts.